Work place: Dept. of ECE, SJCE, Mysore, India
Research Interests: Computational Science and Engineering, Computational Engineering, Engineering
Dr. Shankaraiah received his B.E. degree in Electronics and Communication Engineering from Mysore University, Mysore, India, in 1994, M.Tech. Degree in Digital Electronics and Communication Systems from Mysore University in 1997.He completed Ph.D. under the guidance of Prof. P. Venkataram, Dept. of ECE, IISc.,Bangalore.He has Investigated a transactions based QoS, Resource management schemes for mobile communications environment.
He has more than 18 years of teaching experience in Engineering. He has published more than 30 papers in national and international journals and conferences. He is a reviewer and chair for many conferences. His research interest includes bandwidth management, Quality of Service (QoS) management, topology management, and Energy management for hybrid wireless superstore environments. He is a student member of IEEE and life member of India Society for Technical Education (LMISTE). He is presently working as Professor in the Department of E&C of Sri Jayachamarajendra College of Engineering, Mysuru, and Karnataka, India.
DOI: https://doi.org/10.5815/ijigsp.2018.01.02, Pub. Date: 8 Jan. 2018
With an increase in population of the country day by day and with high growing speed of geographical residential plots, the demand by the public for new set up of electrical power transmission system has become a common mandate. Therefore it is the responsibility of the concerned authority to protect the interests of common man in a smart manner and develop solutions for the growth of country in an intelligent way keeping safety of public as prime importance. This paper proposes an Affine Arithmetic approach of mathematical modelling to estimate the safety parameters of AC transmission line leading to sag, like, temperature, wind loading, ice loading, weight of the conductor, stress, tension, pressure etc., taking into account the uncertainty conditions so that the solutions developed address in real time. The proposed model is executed in MATLAB integrated development environment and gives the complete behavior of sag in transmission lines with respect to each of the safety parameters individually and closely ascertains the safety threshold limits considering 50% factor of safety and 5m ground clearance. The critical safety threshold limit for wind loading is found to be about 3.02 kg/m and the typical value is about 1.51 kg/m. Similarly, the critical safety threshold limit for weight of ice is found to be about 1.45 kg/m, whereas its typical value is about 0.7 kg/m. Extending further, the critical safety threshold limit for conductor weight is found to be about 3.07 kg/m, whereas its typical value is about 1.6 kg/m, which is a close approximation to the typical weight per unit length of industry-grade conductors like Aluminum Conductor Steel Reinforced (ACSR). The critical safety threshold limit for tension in the conductor and the span lengths are found to be 1850 kg and 230m respectively.[...] Read more.
DOI: https://doi.org/10.5815/ijisa.2016.03.07, Pub. Date: 8 Mar. 2016
Many number of real time applications are available for train monitoring using satellite based navigation system with high level of speed and precision. But these systems have faced lot of issues such as multipath loss and line of sight which results in lesser accuracy measurements. When the train is moving in low satellite visible areas such as tunnels, mountains, forest etc, then no position information is available. The service failure in tunnel made big challenge to demonstrate a self supporting innovative platform for navigation of train. This paper is focused on designing a novel approach by integrating Wireless Sensor Network (WSN) and Radio Frequency Identification (RFID) system for continuous monitoring of train moving in tunnel. The wireless tracking controller based on quadratic optimal control theory is considering for analysis. Overall performance of the control design is based on Liapunov approach, where quadratic performance index is directly related to Liapunov functions. By minimizing and maximizing the performance index value corresponding to control inputs will trace the tracking error inaccuracies. As maximizing the performance index, the tracking error produces 0.04% inaccuracy. The data loss is 0.06% when minimizing the performance value. Simulation is carried out using Mat lab.[...] Read more.
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